Personalized autonomous vehicle ride characteristics

ABSTRACT

Systems and method are provided for controlling a vehicle. In one embodiment, a method includes: obtaining ride preference information associated with a user, identifying a current vehicle pose, determining a motion plan for the vehicle along a route based at least in part on the ride preference information, the current vehicle pose, and vehicle kinematic and dynamic constraints associated with the route, and operating one or more actuators onboard the vehicle in accordance with the motion plan. The user-specific ride preference information influences a rate of vehicle movement resulting from the motion plan.

TECHNICAL FIELD

The present disclosure generally relates to autonomous vehicles, andmore particularly relates to systems and methods for personalizing orcustomizing rider experience in an autonomous vehicle.

BACKGROUND

An autonomous vehicle is a vehicle that is capable of sensing itsenvironment and navigating with little or no user input. An autonomousvehicle senses its environment using sensing devices such as radar,light detection and ranging (lidar) devices, image sensors, and thelike. The autonomous vehicle system further uses information from globalpositioning systems (GPS) technology, navigation systems,vehicle-to-vehicle communication, vehicle-to-infrastructure technology,and/or drive-by-wire systems to navigate the vehicle.

Vehicle automation has been categorized into numerical levels rangingfrom Zero, corresponding to no automation with full human control, toFive, corresponding to full automation with no human control. Variousautomated driver-assistance systems, such as cruise control, adaptivecruise control, and parking assistance systems correspond to lowerautomation levels, while true “driverless” vehicles correspond to higherautomation levels.

With traditional manually-controlled vehicles, the vehicle operator iscapable of tailoring the feel of the ride to his or her particulartastes and comfort dynamically and in real-time. However, automatedvehicles operating in a fully autonomous mode may lack the ability torespond to conditions in real-time in a manner that accounts for thetastes or preferences of a particular occupant.

Accordingly, it is desirable to provide systems and methods that allowautomated vehicles to account for occupant preferences and tailor ridecharacteristics. Furthermore, other desirable features andcharacteristics of the present invention will become apparent from thesubsequent detailed description and the appended claims, taken inconjunction with the accompanying drawings and the foregoing technicalfield and background.

SUMMARY

Systems and method are provided for autonomously controlling a vehiclein a personalized manner. In one embodiment, a method includes:obtaining, by a controller onboard the vehicle, ride preferenceinformation associated with a user; identifying, by the controller, acurrent vehicle pose; determining, by the controller, a motion plan forthe vehicle along a route based at least in part on the ride preferenceinformation, the current vehicle pose, one or more constraintsassociated with the route or the vehicle; and operating, by thecontroller, one or more actuators onboard the vehicle in accordance withthe motion plan, wherein the ride preference information influences arate of vehicle movement resulting from the motion plan.

In another embodiment, an autonomous vehicle includes: at least onesensor that provides sensor data; one or more actuators onboard thevehicle; a communication system onboard the vehicle to receive ridepreference information associated with a user; and a controller that, bya processor and based on the sensor data and the ride preferenceinformation, identifies a current vehicle pose, determines objectprediction data for an object based at least in part on the sensor data,determines a motion plan for the vehicle along a route based at least inpart on the ride preference information, the current vehicle pose, theobject prediction data and one or more constraints associated with theroute or the vehicle, and autonomously operates the one or moreactuators onboard the vehicle in accordance with the motion plan,wherein the ride preference information influences a rate of vehiclemovement resulting from the motion plan.

In another embodiment, an autonomous vehicle system includes: agraphical user interface display to receive user input indicative ofride preference information; one or more actuators onboard a vehicle;and a controller onboard the vehicle and coupled to the one or moreactuators to obtain the ride preference information, determine a motionplan for the vehicle along a route based at least in part on the ridepreference information, a current vehicle pose, and one or moreconstraints associated with the route or the vehicle, and operate theone or more actuators onboard the vehicle in accordance with the motionplan, wherein the ride preference information influences a rate ofvehicle movement resulting from the motion plan.

DESCRIPTION OF THE DRAWINGS

The exemplary embodiments will hereinafter be described in conjunctionwith the following drawing figures, wherein like numerals denote likeelements, and wherein:

FIG. 1 is a functional block diagram illustrating an autonomous vehiclehaving a ride control system, in accordance with various embodiments;

FIG. 2 is a functional block diagram illustrating a transportationsystem having one or more autonomous vehicles of FIG. 1, in accordancewith various embodiments;

FIG. 3 is a schematic block diagram of an automated driving system (ADS)for a vehicle in accordance with one or more exemplary embodiments;

FIG. 4 is a block diagram of a motion planning module for a vehicle inaccordance with one or more exemplary embodiments; and

FIG. 5 is a flowchart illustrating a ride characteristic control processfor controlling the autonomous vehicle of FIG. 1, in accordance with oneor more exemplary embodiments.

DETAILED DESCRIPTION

The following detailed description is merely exemplary in nature and isnot intended to limit the application and uses. Furthermore, there is nointention to be bound by any expressed or implied theory presented inthe preceding technical field, background, brief summary or thefollowing detailed description. As used herein, the term module refersto any hardware, software, firmware, electronic control component,processing logic, and/or processor device, individually or in anycombination, including without limitation: application specificintegrated circuit (ASIC), an electronic circuit, a processor (shared,dedicated, or group) and memory that executes one or more software orfirmware programs, a combinational logic circuit, and/or other suitablecomponents that provide the described functionality.

Embodiments of the present disclosure may be described herein in termsof functional and/or logical block components and various processingsteps. It should be appreciated that such block components may berealized by any number of hardware, software, and/or firmware componentsconfigured to perform the specified functions. For example, anembodiment of the present disclosure may employ various integratedcircuit components, e.g., memory elements, digital signal processingelements, logic elements, look-up tables, or the like, which may carryout a variety of functions under the control of one or moremicroprocessors or other control devices. In addition, those skilled inthe art will appreciate that embodiments of the present disclosure maybe practiced in conjunction with any number of systems, and that thesystems described herein is merely exemplary embodiments of the presentdisclosure.

For the sake of brevity, conventional techniques related to signalprocessing, data transmission, signaling, control, and other functionalaspects of the systems (and the individual operating components of thesystems) may not be described in detail herein. Furthermore, theconnecting lines shown in the various figures contained herein areintended to represent example functional relationships and/or physicalcouplings between the various elements. It should be noted that manyalternative or additional functional relationships or physicalconnections may be present in an embodiment of the present disclosure.

With reference to FIG. 1, a ride control system shown generally at 100is associated with a vehicle 10 in accordance with various embodiments.In general, the ride control system 100 determines a motion plan forautonomously operating the vehicle 10 along a route in accordance withride preference information associated with a vehicle occupant. In thisregard, the ride preference information influences the rate at which thevehicle 10 moves laterally and/or longitudinally while traversing theroute and avoiding obstacles, which, in turn influences the rideexperienced by the occupant, as described in greater detail belowprimarily in the context of FIGS. 4-5.

As depicted in FIG. 1, the vehicle 10 generally includes a chassis, abody 14, front wheels 16, and rear wheels 18. The body 14 is arranged onthe chassis and substantially encloses components of the vehicle 10. Thebody 14 and the chassis may jointly form a frame. The wheels 16-18 areeach rotationally coupled to the chassis near a respective corner of thebody 14.

In various embodiments, the vehicle 10 is an autonomous vehicle and theride control system 100 is incorporated into the autonomous vehicle 10(hereinafter referred to as the autonomous vehicle 10). The autonomousvehicle 10 is, for example, a vehicle that is automatically controlledto carry passengers from one location to another. The vehicle 10 isdepicted in the illustrated embodiment as a passenger car, but it shouldbe appreciated that any other vehicle including motorcycles, trucks,sport utility vehicles (SUVs), recreational vehicles (RVs), marinevessels, aircraft, etc., can also be used. In an exemplary embodiment,the autonomous vehicle 10 is a so-called Level Four or Level Fiveautomation system. A Level Four system indicates “high automation”,referring to the driving mode-specific performance by an automateddriving system of all aspects of the dynamic driving task, even if ahuman driver does not respond appropriately to a request to intervene. ALevel Five system indicates “full automation”, referring to thefull-time performance by an automated driving system of all aspects ofthe dynamic driving task under all roadway and environmental conditionsthat can be managed by a human driver.

As shown, the autonomous vehicle 10 generally includes a propulsionsystem 20, a transmission system 22, a steering system 24, a brakesystem 26, a sensor system 28, an actuator system 30, at least one datastorage device 32, at least one controller 34, and a communicationsystem 36. The propulsion system 20 may, in various embodiments, includean internal combustion engine, an electric machine such as a tractionmotor, and/or a fuel cell propulsion system. The transmission system 22is configured to transmit power from the propulsion system 20 to thevehicle wheels 16-18 according to selectable speed ratios. According tovarious embodiments, the transmission system 22 may include a step-ratioautomatic transmission, a continuously-variable transmission, or otherappropriate transmission. The brake system 26 is configured to providebraking torque to the vehicle wheels 16-18. The brake system 26 may, invarious embodiments, include friction brakes, brake by wire, aregenerative braking system such as an electric machine, and/or otherappropriate braking systems. The steering system 24 influences aposition of the of the vehicle wheels 16-18. While depicted as includinga steering wheel for illustrative purposes, in some embodimentscontemplated within the scope of the present disclosure, the steeringsystem 24 may not include a steering wheel.

The sensor system 28 includes one or more sensing devices 40 a-40 n thatsense observable conditions of the exterior environment and/or theinterior environment of the autonomous vehicle 10. The sensing devices40 a-40 n can include, but are not limited to, radars, lidars, globalpositioning systems, optical cameras, thermal cameras, ultrasonicsensors, and/or other sensors. The actuator system 30 includes one ormore actuator devices 42 a-42 n that control one or more vehiclefeatures such as, but not limited to, the propulsion system 20, thetransmission system 22, the steering system 24, and the brake system 26.In various embodiments, the vehicle features can further includeinterior and/or exterior vehicle features such as, but are not limitedto, doors, a trunk, and cabin features such as air, music, lighting,etc. (not numbered).

The data storage device 32 stores data for use in automaticallycontrolling the autonomous vehicle 10. In various embodiments, the datastorage device 32 stores defined maps of the navigable environment. Invarious embodiments, the defined maps may be predefined by and obtainedfrom a remote system (described in further detail with regard to FIG.2). For example, the defined maps may be assembled by the remote systemand communicated to the autonomous vehicle 10 (wirelessly and/or in awired manner) and stored in the data storage device 32. As can beappreciated, the data storage device 32 may be part of the controller34, separate from the controller 34, or part of the controller 34 andpart of a separate system.

The controller 34 includes at least one processor 44 and a computerreadable storage device or media 46. The processor 44 can be any custommade or commercially available processor, a central processing unit(CPU), a graphics processing unit (GPU), an auxiliary processor amongseveral processors associated with the controller 34, a semiconductorbased microprocessor (in the form of a microchip or chip set), amacroprocessor, any combination thereof, or generally any device forexecuting instructions. The computer readable storage device or media 46may include volatile and nonvolatile storage in read-only memory (ROM),random-access memory (RAM), and keep-alive memory (KAM), for example.KAM is a persistent or non-volatile memory that may be used to storevarious operating variables while the processor 44 is powered down. Thecomputer-readable storage device or media 46 may be implemented usingany of a number of known memory devices such as PROMs (programmableread-only memory), EPROMs (electrically PROM), EEPROMs (electricallyerasable PROM), flash memory, or any other electric, magnetic, optical,or combination memory devices capable of storing data, some of whichrepresent executable instructions, used by the controller 34 incontrolling the autonomous vehicle 10.

The instructions may include one or more separate programs, each ofwhich comprises an ordered listing of executable instructions forimplementing logical functions. The instructions, when executed by theprocessor 44, receive and process signals from the sensor system 28,perform logic, calculations, methods and/or algorithms for automaticallycontrolling the components of the autonomous vehicle 10, and generatecontrol signals to the actuator system 30 to automatically control thecomponents of the autonomous vehicle 10 based on the logic,calculations, methods, and/or algorithms. Although only one controller34 is shown in FIG. 1, embodiments of the autonomous vehicle 10 caninclude any number of controllers 34 that communicate over any suitablecommunication medium or a combination of communication mediums and thatcooperate to process the sensor signals, perform logic, calculations,methods, and/or algorithms, and generate control signals toautomatically control features of the autonomous vehicle 10.

In various embodiments, one or more instructions of the controller 34are embodied in the ride control system 100 and, when executed by theprocessor 44, cause the processor 44 to calculate, determine, orotherwise generate a motion plan for operating the vehicle 10 inaccordance with ride preference information. For example, theinstructions may cause the processor 44 to obtain, either from onboardmemory 32 or another entity 48, ride preference information for acurrent vehicle occupant and determine a solution for how to control andtraverse the vehicle 10 along a route in a manner that accounts for theride preference information. Using various longitudinal and lateralconstraints associated with the route (e.g., speed limits or othertraffic restrictions, lane boundaries or other lane restrictions, andthe like), the processor 44 calculates or otherwise determines speed,acceleration, and steering plans for operating the vehicle 10 along theroute in a manner that minimizes a cost (e.g., travel time, fuelconsumption, or the like) associated with traversing the route inaccordance with the ride preference information.

As described in greater detail below in the context of FIGS. 4-5, theride preference information may limit or otherwise constrain the speedor velocity of the vehicle 10 longitudinally (e.g., in the generaldirection of travel along the route), the acceleration or decelerationof the vehicle 10 longitudinally, the longitudinal jerk of the vehicle10 (e.g., rate of change of the acceleration or deceleration of thevehicle 10 longitudinally), the acceleration or deceleration of thevehicle 10 laterally, and/or the rate of change of the acceleration ordeceleration of the vehicle 10 laterally. Additionally, the ridepreference information may limit or otherwise constrain the distance orbuffer maintained between the vehicle 10 and other objects or obstacles,while also indicating which cost variable or combination thereof (e.g.,time, route distance, fuel consumption, or the like) is to be optimizedby the solver. Thus, the resulting longitudinal and lateral motion plansfor the vehicle 10 result in movement of the vehicle that generallycomplies with or otherwise satisfies the occupant's ride characteristicpreferences. For example, the longitudinal plan does not violate themaximum speed or acceleration that is acceptable to the occupant whilealso maintaining a longitudinal separation distance between the vehicle10 and other vehicles or obstacles that satisfies the occupant's desiredminimum following distance. In one or more embodiments, the ridepreference information is constrained by the applicable traffic laws forthe geographic region in which the vehicle 10 is currently located,thereby ensuring the vehicle 10 does not autonomously attempt to violatethe law in order to comply with the ride preference information.

In one or more embodiments, a graphical user interface (GUI) display isprovided that includes GUI elements that allow a user to adjust orotherwise modify his or her ride preference information. The GUI displaymay be generated by the processor 44 on a display device onboard thevehicle or on or by another entity 48, such as, for example, a cellphone, smartphone, or other mobile device communicatively coupled to theprocessor 44 or controller 34. A user may interact with the GUI displayand the GUI elements presented thereon to adjust or otherwise modifyride preferences from initial or default settings and then save orotherwise maintain the ride preference information associated with theuser. Thereafter, the processor 44 retrieves that ride preferenceinformation when the user is in the vehicle 10 and tailors the ridecharacteristics accordingly as described herein. At the completion ofthe route or during the route, the GUI display may be similarlypresented or otherwise provided to the user to thereby allow the user todynamically adjust, update, or otherwise modify his or her ridepreference information substantially in real-time to achieve the desiredride characteristics. In other embodiments, a GUI display may bepresented to obtain ride feedback information from the user, which, inturn may be utilized by the processor 44 or other entity 48 toautomatically adjust the ride preference information associated with theuser based on the ride feedback information from a preceding ride. Thus,the ride preference information may be adapted or otherwise tailored tosuit each individual user's taste or preference.

Still referring to FIG. 1, in exemplary embodiments, the communicationsystem 36 is configured to wirelessly communicate information to andfrom other entities 48, such as but not limited to, other vehicles(“V2V” communication,) infrastructure (“V2I” communication), remotesystems, and/or personal devices (described in more detail with regardto FIG. 2). In an exemplary embodiment, the communication system 36 is awireless communication system configured to communicate via a wirelesslocal area network (WLAN) using IEEE 802.11 standards or by usingcellular data communication. However, additional or alternatecommunication methods, such as a dedicated short-range communications(DSRC) channel, are also considered within the scope of the presentdisclosure. DSRC channels refer to one-way or two-way short-range tomedium-range wireless communication channels specifically designed forautomotive use and a corresponding set of protocols and standards.

With reference now to FIG. 2, in various embodiments, the autonomousvehicle 10 described with regard to FIG. 1 may be suitable for use inthe context of a taxi or shuttle system in a certain geographical area(e.g., a city, a school or business campus, a shopping center, anamusement park, an event center, or the like) or may simply be managedby a remote system. For example, the autonomous vehicle 10 may beassociated with an autonomous vehicle based remote transportationsystem. FIG. 2 illustrates an exemplary embodiment of an operatingenvironment shown generally at 50 that includes an autonomous vehiclebased remote transportation system 52 that is associated with one ormore instances of autonomous vehicles 10 a-10 n as described with regardto FIG. 1. In various embodiments, the operating environment 50 furtherincludes one or more user devices 54 that communicate with theautonomous vehicle 10 and/or the remote transportation system 52 via acommunication network 56.

The communication network 56 supports communication as needed betweendevices, systems, and components supported by the operating environment50 (e.g., via tangible communication links and/or wireless communicationlinks). For example, the communication network 56 can include a wirelesscarrier system 60 such as a cellular telephone system that includes aplurality of cell towers (not shown), one or more mobile switchingcenters (MSCs) (not shown), as well as any other networking componentsrequired to connect the wireless carrier system 60 with a landcommunications system. Each cell tower includes sending and receivingantennas and a base station, with the base stations from different celltowers being connected to the MSC either directly or via intermediaryequipment such as a base station controller. The wireless carrier system60 can implement any suitable communications technology, including forexample, digital technologies such as CDMA (e.g., CDMA2000), LTE (e.g.,4G LTE or 5G LTE), GSM/GPRS, or other current or emerging wirelesstechnologies. Other cell tower/base station/MSC arrangements arepossible and could be used with the wireless carrier system 60. Forexample, the base station and cell tower could be co-located at the samesite or they could be remotely located from one another, each basestation could be responsible for a single cell tower or a single basestation could service various cell towers, or various base stationscould be coupled to a single MSC, to name but a few of the possiblearrangements.

Apart from including the wireless carrier system 60, a second wirelesscarrier system in the form of a satellite communication system 64 can beincluded to provide uni-directional or bi-directional communication withthe autonomous vehicles 10 a-10 n. This can be done using one or morecommunication satellites (not shown) and an uplink transmitting station(not shown). Uni-directional communication can include, for example,satellite radio services, wherein programming content (news, music,etc.) is received by the transmitting station, packaged for upload, andthen sent to the satellite, which broadcasts the programming tosubscribers. Bi-directional communication can include, for example,satellite telephony services using the satellite to relay telephonecommunications between the vehicle 10 and the station. The satellitetelephony can be utilized either in addition to or in lieu of thewireless carrier system 60.

A land communication system 62 may further be included that is aconventional land-based telecommunications network connected to one ormore landline telephones and connects the wireless carrier system 60 tothe remote transportation system 52. For example, the land communicationsystem 62 may include a public switched telephone network (PSTN) such asthat used to provide hardwired telephony, packet-switched datacommunications, and the Internet infrastructure. One or more segments ofthe land communication system 62 can be implemented through the use of astandard wired network, a fiber or other optical network, a cablenetwork, power lines, other wireless networks such as wireless localarea networks (WLANs), or networks providing broadband wireless access(BWA), or any combination thereof. Furthermore, the remotetransportation system 52 need not be connected via the landcommunication system 62, but can include wireless telephony equipment sothat it can communicate directly with a wireless network, such as thewireless carrier system 60.

Although only one user device 54 is shown in FIG. 2, embodiments of theoperating environment 50 can support any number of user devices 54,including multiple user devices 54 owned, operated, or otherwise used byone person. Each user device 54 supported by the operating environment50 may be implemented using any suitable hardware platform. In thisregard, the user device 54 can be realized in any common form factorincluding, but not limited to: a desktop computer; a mobile computer(e.g., a tablet computer, a laptop computer, or a netbook computer); asmartphone; a video game device; a digital media player; a piece of homeentertainment equipment; a digital camera or video camera; a wearablecomputing device (e.g., smart watch, smart glasses, smart clothing); orthe like. Each user device 54 supported by the operating environment 50is realized as a computer-implemented or computer-based device havingthe hardware, software, firmware, and/or processing logic needed tocarry out the various techniques and methodologies described herein. Forexample, the user device 54 includes a microprocessor in the form of aprogrammable device that includes one or more instructions stored in aninternal memory structure and applied to receive binary input to createbinary output. In some embodiments, the user device 54 includes a GPSmodule capable of receiving GPS satellite signals and generating GPScoordinates based on those signals. In other embodiments, the userdevice 54 includes cellular communications functionality such that thedevice carries out voice and/or data communications over thecommunication network 56 using one or more cellular communicationsprotocols, as are discussed herein. In various embodiments, the userdevice 54 includes a visual display, such as a touch-screen graphicaldisplay, or other display.

The remote transportation system 52 includes one or more backend serversystems, which may be cloud-based, network-based, or resident at theparticular campus or geographical location serviced by the remotetransportation system 52. The remote transportation system 52 can bemanned by a live advisor, or an automated advisor, or a combination ofboth. The remote transportation system 52 can communicate with the userdevices 54 and the autonomous vehicles 10 a-10 n to schedule rides,dispatch autonomous vehicles 10 a-10 n, and the like. In variousembodiments, the remote transportation system 52 stores store accountinformation such as subscriber authentication information, vehicleidentifiers, profile records, behavioral patterns, and other pertinentsubscriber information, such as the ride preference informationdescribed herein.

In accordance with a typical use case workflow, a registered user of theremote transportation system 52 can create a ride request via the userdevice 54. The ride request will typically indicate the passenger'sdesired pickup location (or current GPS location), the desireddestination location (which may identify a predefined vehicle stopand/or a user-specified passenger destination), and a pickup time. Theremote transportation system 52 receives the ride request, processes therequest, and dispatches a selected one of the autonomous vehicles 10a-10 n (when and if one is available) to pick up the passenger at thedesignated pickup location and at the appropriate time. Thetransportation system 52 can also generate and send a suitablyconfigured confirmation message or notification to the user device 54,to let the passenger know that a vehicle is on the way.

As can be appreciated, the subject matter disclosed herein providescertain enhanced features and functionality to what may be considered asa standard or baseline autonomous vehicle 10 and/or an autonomousvehicle based remote transportation system 52. To this end, anautonomous vehicle and autonomous vehicle based remote transportationsystem can be modified, enhanced, or otherwise supplemented to providethe additional features described in more detail below.

In accordance with various embodiments, controller 34 implements anautonomous driving system (ADS) 70 as shown in FIG. 3. That is, suitablesoftware and/or hardware components of controller 34 (e.g., processor 44and computer-readable storage device 46) are utilized to provide anautonomous driving system 70 that is used in conjunction with vehicle10, for example, to automatically control various actuators 30 onboardthe vehicle 10 to thereby control vehicle acceleration, steering, andbraking, respectively, without human intervention.

In various embodiments, the instructions of the autonomous drivingsystem 70 may be organized by function or system. For example, as shownin FIG. 3, the autonomous driving system 70 can include a sensor fusionsystem 74, a positioning system 76, a guidance system 78, and a vehiclecontrol system 80. As can be appreciated, in various embodiments, theinstructions may be organized into any number of systems (e.g.,combined, further partitioned, etc.) as the disclosure is not limited tothe present examples.

In various embodiments, the sensor fusion system 74 synthesizes andprocesses sensor data and predicts the presence, location,classification, and/or path of objects and features of the environmentof the vehicle 10. In various embodiments, the sensor fusion system 74can incorporate information from multiple sensors, including but notlimited to cameras, lidars, radars, and/or any number of other types ofsensors.

The positioning system 76 processes sensor data along with other data todetermine a position (e.g., a local position relative to a map, an exactposition relative to lane of a road, vehicle heading, velocity, etc.) ofthe vehicle 10 relative to the environment. The guidance system 78processes sensor data along with other data to determine a path for thevehicle 10 to follow. The vehicle control system 80 generates controlsignals for controlling the vehicle 10 according to the determined path.In one or more exemplary embodiments, the guidance system 78 determinesa vehicle path to be followed to maintain the vehicle on a desired routewhile obeying traffic laws and avoiding any detected obstacles, whilethe vehicle control system 80 generates one or more actuator commandsfor achieving the commanded path, including, but not limited to, asteering command, a shift command, a throttle command, and a brakecommand. By way of example, as illustrated in FIG. 1, the steeringcontrol may control a steering system 24, the shifter control maycontrol a transmission system 22, the throttle control may control apropulsion system 20, and the brake control may control wheel brakesystem 26.

In one or more embodiments, the guidance system 78 provides an outputthat includes a lateral path command for controlling the steering orlateral position of the vehicle along a route and a longitudinal pathcommand for controlling the longitudinal position, the velocity and/orthe acceleration of the vehicle along the route in concert with thelateral path command. In this regard, the lateral and longitudinal pathcommands incorporate or otherwise account for ride preferencesassociated with one or more vehicle occupants to tailor the respectiverates of lateral and longitudinal movement to the preferences of thevehicle occupant(s). For example, for an occupant preferring a moreconservative ride, the longitudinal path command may limit the plannedvelocities and accelerations or increase following distances behindother vehicles or obstacles. Conversely, for an occupant preferring aless conservative ride, the longitudinal path command may utilize lessrestrictive velocities and accelerations or reduce the followingdistances behind other vehicles or obstacles. Similarly, for an occupantpreferring a more conservative ride, the lateral path command may limitthe rates of lateral movement (e.g., by limiting the planned rate ofchange or acceleration of the vehicle steering angle), while for anoccupant preferring a less conservative ride, the lateral path commandmay utilize greater rates of lateral movement.

FIG. 4 depicts a motion planning module 400 suitable for use with avehicle to generate a motion plan for controlling the vehicle as ittraverses along a route, such as, for example, as part of the guidancesystem 78 in an ADS 70 implemented by a control module (e.g., controller34 or processor 44) in the vehicle 10 of FIG. 1. The motion planningmodule 400 includes a longitudinal solver module 402 that generates alongitudinal motion plan output 406 for controlling the movement of thevehicle along the route in the general direction of travel, for example,by causing the vehicle to accelerate or decelerate at one or morelocations in the future along the route. The motion planning module 400also includes a lateral solver module 404 that generates a lateralmotion plan output 408 for controlling the lateral movement of thevehicle along the route to alter the general direction of travel, forexample, by steering the vehicle at one or more locations in the futurealong the route. The longitudinal and lateral plan outputs 406, 408correspond to the commanded (or planned) path output provided to thevehicle control system 80 for controlling the vehicle actuators 30 toachieve movement of the vehicle 10 along the route that corresponds tothe longitudinal and lateral plans 406, 408.

As described above, in exemplary embodiments, the solver modules 402,404 optimize a map of car vehicle trajectories. In this regard, thelongitudinal solver module 402 optimizes the vehicle speed (or velocity)in the direction of travel, the vehicle acceleration in the direction oftravel, and the derivative of the vehicle acceleration in the directionof travel, alternatively referred to herein as the longitudinal jerk ofthe vehicle. The lateral solver module 404 optimizes one or more of thesteering angle, the rate of change of the steering angle, and theacceleration or second derivative of the steering angle, alternativelyreferred to herein as the lateral jerk of the vehicle. In this regard,the steering angle can be related to the curvature of the path or route,and any one of the steering angle, the rate of change of the steeringangle, and the acceleration or second derivative of the steering anglecan be optimized by the lateral solver module 404, either individuallyor in combination.

In exemplary embodiments, the longitudinal solver module 402 receives orotherwise obtains the current or instantaneous pose 410 of the vehicle,which includes the current position or location of the vehicle, thecurrent orientation of the vehicle, the current speed or velocity of thevehicle, and the current acceleration of the vehicle. Using the currentposition or location of the vehicle, the longitudinal solver module 402also retrieves or otherwise obtains route information 412 which includesinformation about the route the vehicle is traveling along given thecurrent pose 410 and plus some additional buffer distance or time period(e.g., 12 seconds into the future), such as, for example, the currentand future road grade or pitch, the current and future road curvature,current and future lane information (e.g., lane types, boundaries, andother constraints or restrictions), as well as other constraints orrestrictions associated with the roadway (e.g., minimum and maximumspeed limits, height or weight restrictions, and the like), includingthose described above or elsewhere within. The route information 412 maybe obtained from, for example, an onboard data storage element 32, anonline database, or other entity. In one or more embodiments, thelateral route information 412 may include the planned lateral pathcommand 408 output by the lateral solver module 404, where thelongitudinal and lateral solver modules 402, 404 iteratively derive anoptimal travel plan along the route as described below.

The longitudinal solver module 402 also receives or otherwise obtainsthe current obstacle data 414 relevant to the route and current pose ofthe vehicle, which may include, for example, the location or position,size, orientation or heading, speed, acceleration, and othercharacteristics of objects or obstacles in a vicinity of the vehicle orthe future route. The longitudinal solver module 402 also receives orotherwise obtains longitudinal vehicle constraint data 416 whichcharacterizes or otherwise defines the kinematic or physicalcapabilities of the vehicle for longitudinal movement, such as, forexample, the maximum acceleration and the maximum longitudinal jerk, themaximum deceleration, and the like. The longitudinal vehicle constraintdata 416 may be specific to each particular vehicle and may be obtainedfrom an onboard data storage element 32 or from a networked database orother entity 48, 52, 54. In some embodiments, the longitudinal vehicleconstraint data 416 may be calculated or otherwise determineddynamically or substantially in real-time based on the current mass ofthe vehicle, the current amount of fuel onboard the vehicle, historicalor recent performance of the vehicle, and/or potentially other factors.In one or more embodiments, the longitudinal vehicle constraint data 416is calculated or determined in relation to the lateral path, the lateralvehicle constraint data 420, and/or determinations made by the lateralsolver module 404. For example, the maximum longitudinal speed may beconstrained at a particular location by the path curvature and themaximum lateral acceleration by calculating the maximum longitudinalspeed as a function of the path curvature and the maximum lateralacceleration (which itself be could be constrained by rider preferencesor vehicle dynamics). In this regard, at locations where the degree ofpath curvature is relatively high (e.g., sharp turns), the maximumlongitudinal speed may be limited accordingly to maintain comfortable orachievable lateral acceleration along the curve.

The longitudinal solver module 402 also receives or otherwise obtainslongitudinal ride preference information 418 associated with aparticular user or vehicle occupant from onboard memory 32 or anotherentity 48, 52, 54 communicatively coupled to a vehicle processingmodule. In this regard, the longitudinal ride preference information 418includes user-specific values or settings for the speed or velocity ofthe vehicle (e.g., a maximum vehicle speed or some other speed targetbased on the speed limit), the acceleration of the vehicle (e.g, amaximum acceleration), the deceleration of the vehicle (e.g., a maximumdeceleration), and the jerk of the vehicle (e.g., maximum jerk in theforward and reverse directions). The longitudinal ride preferenceinformation 418 may include user-specific following distances or buffersbetween objects or obstacles, such as, for example, a minimum and/ormaximum following distance for other vehicles, a minimum buffer orseparation distance between objects or obstacles, and the like.

Using the various inputs 410, 412, 414, 416, 418 to the longitudinalsolver module 402, the longitudinal solver module 402 calculates orotherwise determines a longitudinal plan (e.g., planned speed,acceleration and jerk values in the future as a function of time) fortraveling along the route within some prediction horizon (e.g., 12seconds) by optimizing some longitudinal cost variable or combinationthereof (e.g., minimizing travel time, minimizing fuel consumption,minimizing jerk, or the like) by varying the speed or velocity of thevehicle from the current pose 410 in a manner that ensures the vehiclecomplies with the longitudinal ride preference information 418 to theextent possible while also complying with lane boundaries or other routeconstraints and avoiding collisions with objects or obstacles. In thisregard, in many conditions, the resulting longitudinal plan 406generated by the longitudinal solver module 402 does not violate themaximum vehicle speed, the maximum vehicle acceleration, the maximumdeceleration, and the maximum longitudinal jerk settings associated withthe user, while also adhering to the following distances or buffersassociated with the user. That said, in some scenarios, violating one ormore longitudinal ride preference settings 418 may be necessary to avoidcollisions, comply with traffic signals, or the like, in which case, thelongitudinal solver module 402 may attempt to maintain compliance of asmany of the user-specific longitudinal ride preference settings 418 aspossible. Thus, the resulting longitudinal plan 406 generally complieswith the user's longitudinal ride preference information 418, but doesnot necessarily do so strictly.

Still referring to FIG. 4, in a similar manner, the lateral solvermodule 404 receives or otherwise obtains the current vehicle pose 410and the relevant route information 412 and obstacle data 414 fordetermining a lateral travel plan solution within the predictionhorizon. The lateral solver module 404 also receives or otherwiseobtains lateral vehicle constraint data 420 which characterizes orotherwise defines the kinematic or physical capabilities of the vehiclefor lateral movement, such as, for example, the maximum steering angleor range of steering angles, the minimum turning radius, the maximumrate of change for the steering angle, and the like. The lateral vehicleconstraint data 420 may also be specific to each particular vehicle andmay be obtained from an onboard data storage element 32 or from anetworked database or other entity 48, 52, 54.

The lateral solver module 404 also receives or otherwise obtains theuser-specific lateral ride preference information 422 which includes,for example, user-specific values or settings for the steering rate(e.g., a maximum rate of change for the steering angle, a maximumacceleration of the steering angle, and/or the like), the lateral jerk,and the like. The lateral ride preference information 422 may includealso user-specific distances or buffers, such as, for example, a minimumand/or maximum distance from lane boundaries, a minimum lateral bufferor lateral separation distance between objects or obstacles, and thelike, and potentially other user-specific lane preferences (e.g., apreferred lane of travel).

Using the various inputs 410, 412, 414, 420, 422 to the lateral solvermodule 404, the lateral solver module 404 calculates or otherwisedetermines a lateral plan for traveling along the route at futurelocations within some prediction horizon (e.g., 50 meters) by optimizingsome lateral cost variable or combination thereof (e.g., minimizingdeviation from the center of the roadway, minimizing the curvature ofthe path, minimizing lateral jerk, or the like) by varying the steeringangle or vehicle wheel angle in a manner that ensures the vehiclecomplies with the lateral ride preference information 422 to the extentpossible while also complying with lane boundaries or other routeconstraints and avoiding collisions with objects or obstacles.

In one or more exemplary embodiments, the lateral solver module 404utilizes the longitudinal travel plan 406 from the longitudinal solvermodule 402 along with the route information 412 and obstacle data 414 todetermine how to steer the vehicle from the current pose 410 within theprediction horizon while attempting to comply with the lateral ridepreference information 422.

For example, in some embodiments, the longitudinal solver modules 402,404 iteratively derive an optimal solution for controlling the vehiclealong a future portion of route within a prediction horizon. Forexample, the lateral solver module 404 may generate an initial lateraltravel plan 408 for a lateral prediction horizon based on the currentpose 410, the route information 412 and obstacle data 414, the lateralvehicle constraints 420, and the lateral ride preference information422. Thereafter, the longitudinal solver module 402 may generate aninitial longitudinal travel plan 406 for a longitudinal predictionhorizon that is optimized for a cost variable based on the current pose410 (e.g., the current heading and steering angle) and using the initiallateral travel plan 408 for the steering or orientation of the vehiclealong the route. Thereafter, lateral solver module 404 may generate anupdated lateral travel plan 408 using the initial longitudinal travelplan 406 to inform the vehicle position along the route, and thelongitudinal solver module 402 may similarly generate an updatedlongitudinal travel plan 406 using the updated lateral travel plan 406,and so on, until an optimal combination of longitudinal and lateraltravel plans 406, 408 is achieved that maximizes compliance with theuser's ride preference information 418, 422. In this regard, theresulting longitudinal and lateral travel plans 406, 408 that areultimately output by the motion planning module 400 comply with as manyof the user's ride preferences 418, 422 as possible while optimizing thecost variable and avoiding collisions by varying one or more of thevehicle's velocity, acceleration/deceleration (longitudinally and/orlaterally), jerk (longitudinally and/or laterally), steering angle, andsteering angle rate of change.

The longitudinal travel plan 406 output by the motion planning module400 includes a sequence of planned velocity and acceleration commandswith respect to time for operating the vehicle within the longitudinalprediction horizon (e.g., a velocity plan for the next 12 seconds), andsimilarly, the lateral travel plan 408 output by the motion planningmodule 400 includes a sequence of planned steering angles and steeringrates with respect to distance or position for steering the vehiclewithin the lateral prediction horizon while operating in accordance withthe longitudinal travel plan 406 (e.g., a steering plan for the next 50meters). The longitudinal and lateral plan outputs 406, 408 are providedto the vehicle control system 80, which may utilize vehicle localizationinformation and employs its own control schemes to generate controloutputs that regulate the vehicle localization information to thelongitudinal and lateral plans 406, 408 by varying velocity and steeringcommands provided to the actuators 30, thereby varying the speed andsteering of the vehicle 10 to emulate or otherwise effectuate thelongitudinal and lateral plans 406, 408.

Referring now to FIG. 5, and with continued reference to FIGS. 1-4, adataflow diagram illustrates various embodiments of a ridecharacteristic control process 500 which may be embedded within acontroller 34 in the ride control system 100 of FIG. 1 supporting theADS 70 and motion planning module 400 of FIG. 4 in accordance with thepresent disclosure. As can be appreciated in light of the disclosure,the order of operation within the method is not limited to thesequential execution as illustrated in FIG. 5, but may be performed inone or more varying orders as applicable and in accordance with thepresent disclosure. In various embodiments, the ride characteristiccontrol process 500 can be scheduled to run based on one or morepredetermined events, and/or can run continuously during operation ofthe autonomous vehicle 10.

The illustrated ride characteristic control process 500 initializes bygenerating or otherwise providing one or more GUI displays adapted toallow a user to input or otherwise provide his or her preferences forride characteristics at 502. For example, as described above, the GUIdisplay may be generated by a vehicle control module 34, 44 on a displaydevice onboard the vehicle 10, or alternatively, on the displayassociated with another device 48, 52, 54 accessible to the user. Forexample, the GUI display may be generated by an application on a userdevice 48, 54 that is communicatively coupled to the vehicle controller34 and/or the remote transportation system 52. The GUI display mayinclude GUI elements, such as, for example, slider bars, text boxes,list boxes, and the like. The GUI display may allow for a user to inputor otherwise provide specific values for one or more ride preferencesettings. Alternatively, a user may input or otherwise provideinformation that subjectively characterizes his or her driving or ridingpreferences, which, in turn, may be automatically translated intocorresponding ride preference setting values. For example, a slider barmay be provided that allows the user to move a slider within a range ofpositions from a conservative ride setting to an aggressive ridesetting. Based on the position of the slider bar within the sliderrange, the default setting values for the ride preference settings maybe scaled up or down to achieve more aggressive or more conservativeride preferences.

For example, more aggressive ride settings may result in higher maximumvalues for vehicle speed, acceleration, lateral and longitudinal jerk,steering angle rate, and the like, for example, by multiplying defaultvalues by a scaling factor that is greater than one and determined basedon a position of the slider bar with respect to the slider width. Moreaggressive ride settings may result in lower minimum values forfollowing distance, obstacle buffers or separation distances, separationdistances from a lane boundary or roadway edge, and the like, forexample, by multiplying default values by a scaling factor having afractional value between zero and one that is determined based on aposition of the slider bar with respect to the slider range. Aggressiveride settings may also result in different lane preferences (e.g., theleft lane), or a different cost variable to be optimized by the solvers(e.g., minimize travel time). Conversely, more conservative ridesettings may result in lower maximum values for vehicle speed,acceleration, lateral and longitudinal jerk, steering angle rate, andthe like, for example, by multiplying default values by a scaling factorhaving a fractional value between zero and one based on the sliderposition relative to the conservative end of the slider range. Moreconservative ride settings may also result in higher minimum values forfollowing distance, obstacle buffers or separation distances, separationdistances from a lane boundary or roadway edge, and the like, forexample, by multiplying default values by a scaling factor having avalue greater than one based on the position of the slider bar.Conservative ride settings may also result in different lane preferences(e.g., the right lane), or a different cost variable to be optimized bythe solvers (e.g., minimize fuel consumption).

After the user's ride preferences are defined, the ride characteristiccontrol process 500 continues by storing or otherwise maintaining theuser's ride preference information in association with the user at 504.In this regard, a vehicle control module 34, 44 may store the ridepreference information in a data storage 32 onboard the vehicle 10, oralternatively, the ride preference information may be stored on a mobiledevice 48, 54 associated with the user or on or by a remote device 52 inassociation with the user.

The illustrated process 500 continues by autonomously operating avehicle in accordance with the user's ride preference information at506. For example, as described above, a user may create a ride requestvia the user device 54 which results in the remote transportation system52 dispatching the vehicle 10 to the user's location. In someembodiments, the remote transportation system 52 also utilizesidentification information or other subscriber information associatedwith the user to locate and retrieve the stored ride preferenceinformation associated with that user and then transmits or otherwisetransfers the user's ride preference information to the vehicle controlmodule 34, 44 for subsequent utilization by the ADS 70 and motionplanning module 400. In yet other embodiments, when the user's ridepreference information is stored on a user device 48, 54, the userdevice 48, 54 may establish communications with the vehicle 10 when invicinity of the user device 48, 54 (e.g., via a wireless communicationssession) and then transmits or otherwise transfers the user's ridepreference information from the user device 48, 54 to the vehiclecontrol module 34, 44. In yet other embodiments, the user's ridepreference information may already reside onboard the vehicle 10 instorage 32. Once the user's ride preference information is obtained, thecontroller 34 and/or the processor 44 configures the solver modules 402,404 to utilize the user's ride preference information to generate travelplans 406, 408 to autonomously operate and control travel of the vehicle10 from the initially dispatched location to the desired destinationlocation in accordance with the ride preference information.

In exemplary embodiments, the ride characteristic control process 500generates or otherwise provides one or more GUI displays adapted toallow a user to input or otherwise provide feedback regarding the ridequality resulting from the autonomous operation of the vehicle at 508and adjusts or otherwise updates the user's ride preference informationin response to the ride feedback at 510. For example, either duringautonomous operation of the vehicle 10 or upon reaching the desireddestination, a GUI display may be generated on a display device onboardthe vehicle 10 or on a user device 48, 54 that allows the user toprovide feedback regarding the ride quality or otherwise adjust his orher ride preferences. In this regard, the GUI display may be the same asor different from the GUI display generated at 502. In one embodiment,the GUI display prompts the user to provide feedback as to whether ornot the user perceived the ride to be too aggressive or tooconservative. Based on the response received from the user, the ridecharacteristic control process 500 adjusts the user's ride preferenceinformation to be more aggressive (e.g., when the ride is tooconservative) or more conservative (e.g., when the ride is tooaggressive), for example, by scaling values up or down accordingly asdescribed above. In one or more exemplary embodiments, the loop definedby 506, 508 and 510 repeats indefinitely to dynamically adjust orotherwise adapt a user's ride preferences to fine tune the user's ridepreference settings values to suit the tastes of that particular user.

In one or more exemplary embodiments, the ride characteristic controlprocess 500 stores or otherwise maintains the updated ride preferenceinformation in lieu of the preceding ride preference information in asimilar manner as described above at 504. In yet other embodiments, theride characteristic control process 500 may store or otherwise maintainone or more historical ride preference settings for the user tocalculate or otherwise determine updated ride preference settings forthe user as a weighted sum of preceding values for the respective ridecharacteristics. In this regard, it should be noted that in practice,there are numerous different ways that the ride characteristic controlprocess 500 can dynamically adjust a user's ride preference informationto adaptively respond to the user's ride quality feedback and arrive atride preference settings that are uniquely tailored for that particularuser.

It will be appreciated that the subject matter described herein allowsfor autonomous vehicle operation to be tailored and achieve a ridequality in accordance with each individual user's ride preferences.Thus, the user experience is improved when riding in an autonomousvehicle. It should also be noted that in practice, the subject mattermay be described herein may also account for multiple different users inthe same vehicle. For example, in various embodiments, when there aremultiple user's in a vehicle, the ride preference information may beobtained for each of the users and averaged or otherwise combined toachieve cumulative ride preference settings that account for therelative preferences of each of the users. Feedback regarding thecumulative ride preference settings may also be utilized to adjust orotherwise alter individual user ride preference settings in a similarmanner as described above. For example, in various embodiments, a GUIdisplay may be presented or provided to an individual user that promptsthe user for whether or not the user wants to modify or update theirride preferences, and if so, the individual user ride preferencesettings may be automatically updated according to the feedback (e.g.,by weighting the user's previous preferences with the cumulativepreferences or isolating the individual user's feedback) or a GUIdisplay (or sequence thereof) may be provided that allows the individualto further refine his or her ride preferences. In this regard, there arenumerous different ways in which the ride preferences may be dynamicallyor adaptively updated, and the subject matter described herein is notintended to be limited to any particular manner or technique.

While at least one exemplary embodiment has been presented in theforegoing detailed description, it should be appreciated that a vastnumber of variations exist. It should also be appreciated that theexemplary embodiment or exemplary embodiments are only examples, and arenot intended to limit the scope, applicability, or configuration of thedisclosure in any way. Rather, the foregoing detailed description willprovide those skilled in the art with a convenient road map forimplementing the exemplary embodiment or exemplary embodiments. Itshould be understood that various changes can be made in the functionand arrangement of elements without departing from the scope of thedisclosure as set forth in the appended claims and the legal equivalentsthereof.

What is claimed is:
 1. A method of autonomously controlling a vehicle ina personalized manner, the method comprising: obtaining, by a controlleronboard the vehicle, ride preference information associated with a user,the ride preference information comprising a user-specific value for amaximum rate of change for an acceleration of the vehicle; identifying,by the controller, a current vehicle pose; determining, by thecontroller, a motion plan for the vehicle along a route based at leastin part on the ride preference information, the current vehicle pose,and constraints associated with the route, wherein the motion plancomprises a solution for traversing along the route from the currentvehicle pose in a manner that satisfies the constraints and theuser-specific value for the maximum rate of change for the accelerationof the vehicle, the user-specific value for the maximum rate of changefor the acceleration of the vehicle influencing a rate of vehiclemovement resulting from the motion plan; and operating, by thecontroller, one or more actuators onboard the vehicle in accordance withthe motion plan.
 2. The method of claim 1, the ride preferenceinformation including a longitudinal constraint, wherein thelongitudinal constraint influences the rate of vehicle movementlongitudinally.
 3. The method of claim 1, the ride preferenceinformation including a lateral constraint, wherein the lateralconstraint influences the rate of vehicle movement laterally.
 4. Themethod of claim 1, further comprising obtaining, by the controller,obstacle data for an object, wherein: the ride preference informationincludes a separation distance; and the separation distance influencesthe rate of vehicle movement relative to the object.
 5. The method ofclaim 1, the ride preference information comprising a plurality ofconstraints, wherein determining the motion plan comprises determining asolution for traversing along the route from the current vehicle posethat maximizes compliance with the plurality of constraints.
 6. Themethod of claim 5, wherein determining the solution comprises optimizinga cost function associated with traversing along the route from thecurrent vehicle pose in a manner that maximizes compliance with theplurality of constraints.
 7. The method of claim 1, further comprising:receiving user feedback after operating the one or more actuators inaccordance with the motion plan; and updating the ride preferenceinformation based on the user feedback.
 8. The method of claim 1,wherein obtaining the ride preference information comprises receivingthe ride preference information from a user device in a vicinity of thevehicle.
 9. The method of claim 1, wherein obtaining the ride preferenceinformation comprises receiving the ride preference informationassociated with the user from a remote device via a network.
 10. Themethod of claim 1, wherein obtaining the ride preference informationcomprises: generating a graphical user interface display including oneor more graphical user interface elements; and receiving the ridepreference information input via the one or more graphical userinterface elements.
 11. A computer-readable medium havingcomputer-executable instructions stored thereon that, when executed by aprocessor of the controller onboard the vehicle, cause the processor toperform the method of claim
 1. 12. An autonomous vehicle, comprising: atleast one sensor that provides sensor data; one or more actuatorsonboard the vehicle; a communication system onboard the vehicle toreceive ride preference information associated with a user, the ridepreference information comprising a user-specific value for a maximumrate of change for an acceleration of the vehicle; and a controllerthat, by a processor and based on the sensor data and the ridepreference information, identifies a current vehicle pose, determinesobject prediction data for an object based at least in part on thesensor data, determines a motion plan for the vehicle along a routebased at least in part on the ride preference information, the currentvehicle pose, the object prediction data and constraints associated withthe route, and autonomously operates the one or more actuators onboardthe vehicle in accordance with the motion plan, wherein: the motion plancomprises a solution for traversing along the route from the currentvehicle pose in a manner that satisfies the constraints and theuser-specific value for the maximum rate of change for the accelerationof the vehicle; and the user-specific value for the maximum rate ofchange for the acceleration of the vehicle influences a rate of vehiclemovement resulting from the motion plan.
 13. The vehicle of claim 12,the ride preference information comprising a plurality of constraints,wherein the motion plan comprises a solution for traversing along theroute from the current vehicle pose that maximizes compliance with theplurality of constraints.
 14. The vehicle of claim 13, wherein theplurality of constraints includes one or more of a maximum speed, amaximum acceleration, or a maximum longitudinal jerk influencing therate of vehicle movement longitudinally.
 15. The vehicle of claim 13,wherein the plurality of constraints includes at least one of a maximumsteering rate, a maximum steering rate acceleration, a maximum lateralacceleration, and a maximum lateral jerk influencing the rate of vehiclemovement laterally.
 16. The vehicle of claim 13, wherein the pluralityof constraints includes at least one of a minimum lateral separationdistance and a minimum following distance, wherein the at least one ofthe minimum lateral separation distance and the minimum followingdistance influences the rate of vehicle movement relative to the object.17. The vehicle of claim 12, wherein the controller is configured toreceive user feedback via the communications system after operating theone or more actuators in accordance with the motion plan and update theride preference information based on the user feedback.
 18. Anautonomous vehicle system comprising: a graphical user interface displayto receive user input indicative of ride preference information, theride preference information comprising a user-specific value for amaximum rate of change for an acceleration of the vehicle; one or moreactuators onboard a vehicle; and a controller onboard the vehicle andcoupled to the one or more actuators to obtain the ride preferenceinformation, determine a motion plan for the vehicle along a route basedat least in part on the ride preference information, a current vehiclepose, and constraints associated with the route, and operate the one ormore actuators onboard the vehicle in accordance with the motion plan,wherein: the motion plan comprises a solution for traversing along theroute from the current vehicle pose in a manner that satisfies theconstraints and the user-specific value for the maximum rate of changefor the acceleration of the vehicle; and the user-specific value for themaximum rate of change for the acceleration of the vehicle influences arate of vehicle movement resulting from the motion plan.
 19. The systemof claim 18, further comprising one or more sensors onboard the vehicleto provide sensor data, wherein: the controller is configured todetermine object prediction data for an object based at least in part onthe sensor data and determines the motion plan based at least in part onthe ride preference information, the current vehicle pose, the objectprediction data and the constraints associated with the route; and theride preference information influences the rate of vehicle movementrelative to the object.
 20. The system of claim 18, the ride preferenceinformation comprising a plurality of constraints, wherein the motionplan comprises an optimal solution for traversing along the route fromthe current vehicle pose that satisfies the plurality of constraints.